When an expert labels a scan, an auditor flags a vulnerability, or a model makes a call, PoQ answers the question every AI team asks: who reviewed this, and can the review be trusted? A panel of independent experts scores each item against your rubric, and the result is sealed as a permanent, auditable record.

Proof of Quality (PoQ) is a verification layer for AI work. You define quality as a rubric, a panel of independent validators scores each item against it, consensus resolves one verdict per item, and PoQ seals the rubric, outcome, and level of agreement as a permanent onchain attestation. Instead of asking anyone to trust an internal review process, PoQ records how the decision was reached — and anyone can verify that record.

PoQ sits on top of the evaluation, audit, and review workflows you already run. It doesn't replace your tools or experts; it preserves how quality was judged so the claim can travel with the work.

A score tells you what was decided, not why. As AI work moves between teams and organizations, customers, partners, auditors, and regulators inherit the conclusion — but rarely the standard, the evidence, or the level of agreement behind it. PoQ attaches that record to the claim itself, so a quality claim no longer depends on the credibility of whoever made it.

Having experts review every item is the gold standard — and it is slow and expensive. PoQ makes the fast path trustworthy instead: panels mix human experts with AI agent validators, consensus resolves each item, and only split panels escalate to experts. Both kinds of validators see the same rubric and evidence and are scored the same way. The attestation is what makes this automation viable — you don't have to trust the automated review, because you can verify it.

You bring intent and a folder of data. PoQ returns a signed PoQ Report: one verifiable record of what was reviewed, by whom, against what rubric, and with how much agreement.

Proof of Quality is Sapien's core contribution to the infrastructure of AI data. It is a structured signal of trust that emerges from contributor behavior, peer validation, and onchain financial alignment. When tasks require real-world expertise, we verify credentials — that includes doctors, engineers, lawyers, and other professionals. But we do not rely on institutional status alone to enforce quality.

Before a contributor can complete complex tasks, they must lock a portion of their $SAPIEN tokens as collateral. This stake serves as a performance guarantee.